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Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam Questions
- Salesforce Consultant Certifications
- Salesforce CRM Analytics and Einstein Discovery Consultant Certifications
- Topic 1: Data Layer: In this comprehensive section, Salesforce consultants delve into the heart of data extraction and loading. It's all about showcasing a deep understanding of implementing refreshes for data syncs, performing data transformations, and implementing delivery management strategies in dataflows.
- Topic 2: Security: Consultants stepping into this section will showcase their prowess in implementing necessary security settings. It covers critical aspects such as suitable dataset security settings, and the ability to implement app sharing.
- Topic 3: Admin/Configuration: This topic takes Salesforce consultants on a journey through the enablement of CRM Analytics. It tests their ability to design a solution that is suitable for data sync/dataflows/recipe limits.
- Topic 4: Analytics Dashboard Implementation: Here, consultants embark on a creative exploration of dashboard configuration, optimization of query performance using Dashboard Inspector, and using advanced functionality such as windowing.
- Topic 5: Analytics Dashboard Design: Building upon the design foundation, this section challenges candidates to bring their dashboard designs to life. It covers the technical expertise required to scope, validate, and prioritize dashboard design requirements.
- Topic 6: Einstein Discovery: This section unveils the magic of AI-driven insights and candidates' ability to analyze and choose one of the three types of predictions. It involves leveraging Einstein's advanced analytics capabilities to adjust data parameters, add or remove data and columns for the improvement of the model.
Free Salesforce Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) Exam Actual Questions
Note: Premium Questions for Salesforce Certified CRM Analytics and Einstein Discovery Consultant (Analytics-Con-201) were last updated On Aug. 06, 2025 (see below)
The CRM Analytics consultant at Universal Containers has set data syncs and recipe runs back to back. However, they notice that the data syncs and recipe run jobs fail repeatedly. Upon investigation,
they realize the data syncs and recipes are tightly coupled which leads to too many runs being queued and eventually being canceled.
How should the consultant resolve this issue?
Universal Containers has a well-defined role hierarchy in Salesforce where everyone is assigned to an appropriate node. The accounts within their instance are categorized by their demography.
An individual sales rep should be able to view all accounts that they own. In addition, sales reps should be able to see any accounts where the value of the account demography matches the demography defined on their user record. A user could have more than one demography defined on their user record.
To meet this requirement, the CRM Analytics consultant has set up a security predicate of the existing 'Account' dataset as follows:
This, however, does not seem to be working as expected.
What is causing the issue?
The issue with the security predicate not functioning as expected likely stems from a permissions issue related to the custom field Demographic__c on the User object. Here's a detailed explanation:
Field-Level Security: If the sales reps do not have access to the Demographic__c field, the security predicate which references this field cannot execute properly as the system cannot evaluate the predicate without accessing the field.
Permission Settings: Ensuring that the sales reps have the necessary permissions to view and use the Demographic__c field is crucial for the security predicate to function correctly.
Data Visibility: The security model in CRM Analytics relies heavily on the underlying data permissions in Salesforce. If these permissions are not correctly configured, the expected data visibility through CRM Analytics will not be achieved.
A system administrator and a CRM Analytics consultant are working together on deploying arecipe/dataflow and a dataset to another org. Prior to this deployment, a package was deployed with all the custom fields used in the dataflow and dataset.
While running the recipe/dataflow in the target environment, the consultant encounters multiple errors related to these custom fields.
How should this be resolved?
A CRM Analytics consultant has been asked to bring data from an external database as well as five external Salesforce environments into CRM Analytics. Twenty-five objects have been enabled from the local Salesforce connector.
The requirements are:
* 10 objects should be enabled from an external database
* 12 objects each from three of the external Salesforce environments
* 15 objects each from the remaining two external Salesforce environments
The consultant estimates each connector will, per object, bring between 1,000 and 1 million rows of data.
Which limit will be exceeded?
In evaluating the scenario presented where multiple external sources and objects are being integrated into CRM Analytics, we need to consider the total number of enabled objects across all connections. Here's a breakdown:
10 objects from an external database
12 objects each from three external Salesforce environments, totaling 36 objects
15 objects each from two external Salesforce environments, totaling 30 objects
25 objects already enabled from the local Salesforce connector
This brings us to a total of 101 objects enabled, which may exceed typical limits on the number of objects that can be enabled in a CRM Analytics environment, depending on the specific Salesforce licensing and platform limits.
Which capability can a consultant use if ''Deploy without connecting to a Salesforce Object'' is selected while deploying the model?
When deploying a model with the option 'Deploy without connecting to a Salesforce Object', the suitable capabilities include:
Use of Predict Function in Salesforce Flows: This capability allows the deployed model to be used within Salesforce Flow as a predictive tool, enabling automation flows to include predictions without directly writing back to Salesforce objects.
Flexibility in Application: This method provides flexibility in how predictions are utilized across various Salesforce processes and workflows, without the need for direct data manipulation within Salesforce objects.
Enhanced Workflow Integration: By integrating predictive insights directly into flows, organizations can automate decision-making processes, enhance user interactions, and streamline operations based on predictive outcomes.
This setup aligns with Salesforce's best practices for leveraging CRM Analytics to enhance operational efficiency and decision accuracy across different business functions.
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